Sub-spatial resolution position estimation for optical fibre sensing applications

Darko Zibar, Stefan Werzinger, Bernhard Schmauss

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Methods from machine learning community are employed for estimating the position of fibre Bragg gratings in an array. Using the conventional methods for position estimation, based on inverse discrete Fourier transform (IDFT), it is required that two-point spatial resolution is less than gratings' spacing. However, we show that by employing statistical inference methods in combination with adaptive gradient algorithm, it is still possible to estimate the grating positions even though this requirement is violated. No prior knowledge of the reflection coefficients is needed as the joint estimation of reflection coefficients and the positions is performed. From the practical point of view, we can demonstrate the reduction of the interrogator's bandwidth by factor of 2. The technique is demonstrated for incoherent optical frequency domain reflectometry (IOFDR). However, the approach is applicable to any other OFDR technique where bandwidth-resolution limitations of IDFT apply.
    Original languageEnglish
    Title of host publicationProceedings of 16th IEEE SENSORS Conference
    Number of pages3
    PublisherIEEE
    Publication date2017
    Pages1-3
    ISBN (Print)9781509010127
    DOIs
    Publication statusPublished - 2017
    EventIEEE Sensors 2017 - Scottish Event Campus, Glasgow, United Kingdom
    Duration: 30 Oct 20171 Nov 2017
    https://ieeexplore.ieee.org/xpl/conhome/8169642/proceeding

    Conference

    ConferenceIEEE Sensors 2017
    LocationScottish Event Campus
    Country/TerritoryUnited Kingdom
    CityGlasgow
    Period30/10/201701/11/2017
    Internet address

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